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Methods for Computational Gene Prediction (Englisch) Gebundene Ausgabe – 16. August 2007

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"... groundbreaking book..."

Über das Produkt

This advanced text describes in detail the algorithms and models used to identify genes in genomic DNA sequences. It provides the underlying theory of both established techniques and also methods at the forefront of current research and is ideal for use in a first course in bioinformatics or computational biology.

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Die hilfreichsten Kundenrezensionen auf Amazon.com (beta)

Amazon.com: HASH(0x96d2e138) von 5 Sternen 8 Rezensionen
4 von 4 Kunden fanden die folgende Rezension hilfreich
HASH(0x96ef2e70) von 5 Sternen An Extraordinary Addition to the Bioinformatics Bookshelf 19. November 2007
Von B-man - Veröffentlicht auf Amazon.com
Format: Taschenbuch
If you are interested in bioinformatics and the art of gene prediction or genome annotation, you MUST buy this book!! Methods for Computational Gene Prediction was written with both molecular biologists and computer scientists in mind. Although those with training in math and statistics will find some of the material easier to grasp, the book starts out with both a math primer and background on molecular biology to bring both target audiences up to speed. The author, Bill Majoros, did a fantastic job at describing gene prediction methods and walks the reader through examples by providing numerous illustrations and blocks of pseudocode. My personal favorite is the chapter on the `Toy Exon Finder', which really sets the stage for studying the art of gene prediction. The book is structured so that it can be used as a textbook for a course in bioinformatics, with problem sets provided at the end of each chapter. Although there are many books that focus on topics in bioinformatics, this is most definitely one of my favorites, alongside Durbin and Eddy's Biological Sequence Analysis, another essential text for anyone in this field.
2 von 2 Kunden fanden die folgende Rezension hilfreich
HASH(0x976d0a08) von 5 Sternen Fantastic resource 21. November 2009
Von Adam M. Phillippy - Veröffentlicht auf Amazon.com
Format: Taschenbuch
This is a fantastic reference on a complex, yet fundamental, problem in genomics. Computational gene prediction is a foundational aspect of modern genomics, yet it is hard to find a one-stop-shop to learn what it is all about. This book provides that all-in-one resource, covering the general biological, mathematical, and machine learning backgrounds alongside the detailed and clear explanations of gene finding. The book also includes many helpful examples, with pseudocode, making it ideal for a class textbook. After working through the examples I came away not only with a clear understanding, but with my own functioning gene finder! This is an excellent book that provides the kind of detail not found in the journals, along with lots of tips and tricks accumulated by the author that can't be found elsewhere. I highly recommend it.
1 von 1 Kunden fanden die folgende Rezension hilfreich
HASH(0x96c74414) von 5 Sternen A great reference both for gene prediction and for many basic bioinformatics techniques 27. Februar 2008
Von M. Eaton - Veröffentlicht auf Amazon.com
Format: Taschenbuch
I recently sat down to tackle a problem in bioinformatics that was just begging for a hidden markov model with Baum Welch to estimate the emissions and transition probabilities. I had two books at my fingertips: this one and Durbin. I have to say, I found this the more helpful of the two. The explanations are on par with each other but this book takes a slightly more computationally focused approach and provides very clear pseudo-code for all of its more complicated algorithms (Baum Welch, forward, backward, viterbi, etc.). I found it indispensable as a computational reference.

I don't want to give the impression that all this book is good for is hidden markov models, either, though a hefty portion of the book is dedicated to them. It also contains reviews of probability theory, statistics and various machine learning techniques aside from HMMs that are equally clear. I'm not saying that this replaces Durbin, since the focus isn't the same, but it's a great bioinformatics book nonetheless and has won a permanent spot on my shelf.
1 von 1 Kunden fanden die folgende Rezension hilfreich
HASH(0x96c748a0) von 5 Sternen Easy to read, great bioinfomatics book! 1. September 2009
Von S. Munshaw - Veröffentlicht auf Amazon.com
Format: Taschenbuch
I wanted to learn about implementing HMMs to a particular problem and this book was extremely useful for that. The explanations, though mathematical are simple and straightforward. It is an easy read and provides a great reference for various bioinformatic tools.
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HASH(0x96c74f18) von 5 Sternen Excellent Text 19. November 2008
Von Gerald W. Perham - Veröffentlicht auf Amazon.com
Format: Taschenbuch
Well-written and at the right level - not so simple that you are bored and not so complex that you cannot follow. Enjoyable to anyone interested in science.
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